Modeling the length of day and extrapolating the rotation of the Earth

The stochastic behavior of the length of day (LOD) process is analyzed and is modeled within statistical accuracy on a time-scale ranging from weeks to millennia by a three-component model comprising a global Brownian motion process, decadal fluctuations, and a 50-day Madden–Julian oscillation. While the model is intended to be phenomenological, some possible physical models underlying the three components are speculated upon. The model is applied to estimate long-range extrapolation errors. For example, it predicts a standard error of 1 h in the clock-time correction ΔT for extrapolation by 1,500 years from 500 to 2000 BC.     

Hydrodynamic simulations of merging clusters of galaxies

We present the results of high-resolution AP³M+SPH simulations of merging clusters of galaxies. We find that the compression and shocking of the core gas during a merger can lead to large increases in bolometric X-ray luminosities and emission-weighted temperatures of clusters. Cooling flows are completely disrupted during equal-mass mergers, with the mass deposition rate dropping to zero as the cores of the clusters collide. The large increase in the cooling time of the core gas strongly suggests that cooling flows will not recover from such a merger within a Hubble time. Mergers with subclumps having one eighth of the mass of the main cluster are also found to disrupt a cooling flow if the merger is head-on. However, in this case the entropy injected into the core gas is rapidly radiated away and the cooling flow restarts within a few Gyr of the merger. Mergers in which the subcluster has an impact parameter of 500 kpc do not disrupt the cooling flow, although the mass deposition rate is reduced by ∼30 per cent. Finally, we find that equal mass, off-centre mergers can effectively mix gas in the cores of clusters, while head on mergers lead to very little mixing. Gas stripped from the outer layers of subclumps results in parts of the outer layers of the main cluster being well mixed, although they have little effect on the gas in the core of the cluster. None of the mergers examined here resulted in the intracluster medium being well mixed globally.     

Geomasking sensitive health data and privacy protection: an evaluation using an E911 database

Geomasking is used to provide privacy protection for individual address information while maintaining spatial resolution for mapping purposes. Donut geomasking and other random perturbation geomasking algorithms rely on the assumption of a homogeneously distributed population to calculate displacement distances, leading to possible under-protection of individuals when this condition is not met. Using household data from 2007, we evaluated the performance of donut geomasking in Orange County, North Carolina. We calculated the estimated k-anonymity for every household based on the assumption of uniform household distribution. We then determined the actual k-anonymity by revealing household locations contained in the county E911 database. Census block groups in mixed-use areas with high population distribution heterogeneity were the most likely to have privacy protection below selected criteria. For heterogeneous populations, we suggest tripling the minimum displacement area in the donut to protect privacy with a less than 1% error rate.     

A multiple indicator, multiple cause method for representing social capital with an application to psychological distress

This paper describes a structural equation methodology for obtaining social capital scores for survey subjects from multiple indicators of social support, neighbourhood and trust perceptions, and memberships of organizations. It adjusts for variation that is likely to occur in levels of social capital according to geographic context (e.g. level of area deprivation, geographic region, level of urbanity) and demographic group. Social capital is used as an explanatory factor for psychological distress using data from the 2006 Health Survey for England. A highly significant effect of social capital in reducing the chance of psychiatric caseness is obtained after controlling for other individual and geographic risk factors. Allowing for social capital has considerable effects on the impacts on psychiatric health of other risk factors. In particular, the impact of area deprivation category is much reduced. There is also evidence of significant differentiation in social capital between population categories and geographic contexts.     

Participation in higher education: A geodemographic perspective on the potential for further expansion in student numbers

Higher education in England has expanded rapidly in the last ten years with the result that currently more than 30% of young people go on to university. Expansion is likely to continue following the recommendations of a national committee of inquiry (the Dearing Committee). The participation rate is known to vary substantially among social groups and between geographical areas. In this paper the participation rate is calculated using a new measure, the Young Entrants Index (YEI), and the extent of variation by region, gender and residential neighbourhood type established. The Super Profiles geodemographic system is used to facilitate the latter. This is shown to be a powerful discriminator and to offer great potential as an alternative analytical approach to the conventional social class categories, based on parental occupation, that have formed the basis of most participation studies to date. Received: 20 October 1998/Accepted: 5 May 1999     

Seeing Conditions at Sutherland. Results of the 1992/93 seeing campaign

In order to decide whether the seeing conditions at SAAO/Sutherland justify the erection of a 3.5 m telescope and also to compare Sutherland with the Gamsberg/Namibia site, a seeing campaign covering 15 months has been carried out. For direct comparison with the results of the seeing campaign at Gamsberg twenty years before the same QUESTAR telescope was employed. The seeing is determined by the scattering of the star-trail exposed on a film in the focal plane of the telescope. The campaign commenced in February 1992. Up to May 1993, data for 204 nights, that is 47.3% of the total number of nights, were collected. Due to wind speeds above 30 km h^-1, 25 out of the 204 nights were not considered in the final reduction. The useful 179 nights are evenly distributed over the campaign period. The median seeing value for the whole period is = 0.52. There are differences during the year: the best season gives = 0.42, the worst = 0.67. Each night was divided into three intervals, although data for each of the three intervals were not always available. Generally, there is an improvement in the seeing during the course of a night. The results are compared to the seeing values of Gamsberg/Namibia and ESO/La Silla.     

Post‐orogenic evolution of the southern Pyrenees: constraints from inverse thermo‐kinematic modelling of low‐temperature thermochronology data

The late‐stage evolution of the southern central Pyrenees has been well documented but controversies remain concerning potential Neogene acceleration of exhumation rates and the influence of tectonic and/or climatic processes. A popular model suggests that the Pyrenees and their southern foreland were buried below a thick succession of conglomerates during the Oligocene, when the basin was endorheic. However, both the amount of post‐orogenic fill and the timing of re‐excavation remain controversial. We address this question by revisiting extensive thermochronological datasets of the Axial Zone. We use an inverse approach that couples the thermo‐kinematic model Pecube and the Neighbourhood inversion algorithm to constrain the history of exhumation and topographic changes since 40 Ma. By comparison with independent geological data, we identified a most probable scenario involving rapid exhumation (>2.5 km Myr^?1) between 37 and 30 Ma followed by a strong decrease to very slow rates (0.02 km Myr^?1) that remain constant until the present. Therefore, the inversion does not require a previously inferred Pliocene acceleration in regional exhumation rates. A clear topographic signal emerges, however: the topography has to be infilled by conglomerates to an elevation of 2.6 km between 40 and 29 Ma and then to remain stable until ca. 9 Ma. We interpret the last stage of the topographic history as recording major incision of the southern Pyrenean wedge, due to the Ebro basin connection to the Mediterranean, well before previously suggested Messinian ages. These results thus demonstrate temporally varying controls of different processes on exhumation: rapid rock uplift in an active orogen during late Eocene, whereas base‐level changes in the foreland basin control the post‐orogenic evolution of topography and exhumation in the central Pyrenees. In contrast, climate changes appear to play a lesser role in the post‐orogenic topographic and erosional evolution of this mountain belt.     

Space-Time Intelligence Systems: Technology, applications and methods

Geographic Information System (GIS) software is constrained, to a greater or lesser extent, by a static world view that is not well-suited to the representation of time (Goodchild 2000). Space Time Intelligence System (STIS) software holds the promise of relaxing some of the technological constraints of spatial only GIS, making possible visualization approaches and analysis methods that are appropriate for temporally dynamic geospatial data. This special issue of the Journal of Geographical Systems describes some recent advances in STIS technology and methods, with an emphasis on applications in public health and spatial epidemiology.The STIS expert workshops were funded in part by grants R01CA092669 and R01CA096002 from the National Cancer Institute, and by grants R43-ES010220 and R44-ES010220 from the National Institute of Environmental Health Sciences. Gillian AvRuskin provided cheerful editorial assistance. We thank the participants at the workshops for providing invaluable expertise and critical insights.     

Self-organised clustering for road extraction in classified imagery

The extraction of road networks from digital imagery is a fundamental image analysis operation. Common problems encountered in automated road extraction include high sensitivity to typical scene clutter in high-resolution imagery, and inefficiency to meaningfully exploit multispectral imagery (MSI). With a ground sample distance (GSD) of less than 2 m per pixel, roads can be broadly described as elongated regions. We propose an approach of elongated region-based analysis for 2D road extraction from high-resolution imagery, which is suitable for MSI, and is insensitive to conventional edge definition. A self-organising road map (SORM) algorithm is presented, inspired from a specialised variation of Kohonen's self-organising map (SOM) neural network algorithm. A spectrally classified high-resolution image is assumed to be the input for our analysis. Our approach proceeds by performing spatial cluster analysis as a mid-level processing technique. This allows us to improve tolerance to road clutter in high-resolution images, and to minimise the effect on road extraction of common classification errors. This approach is designed in consideration of the emerging trend towards high-resolution multispectral sensors. Preliminary results demonstrate robust road extraction ability due to the non-local approach, when presented with noisy input.     

Non-stationary Approaches for Mapping Terrain and Assessing Prediction Uncertainty

It is well known that terrain may vary markedly over small areas and that statistics used to characterise spatial variation in terrain may be valid only over small areas. In geostatistical terminology, a non-stationary approach may be considered more appropriate than a stationary approach. In many applications, local variation is not accounted for sufficiently. This paper assesses potential benefits in using non-stationary geostatistical approaches for interpolation and for the assessment of uncertainty in predictions with implications for sampling design. Two main non-stationary approaches are employed in this paper dealing with (1) change in the mean and (2) change in the variogram across the region of interest. The relevant approaches are (1) kriging with a trend model (KT) using the variogram of residuals from local drift and (2) locally-adaptive variogram KT, both applied to a sampled photogrammetrically derived digital terrain model (DTM). The fractal dimension estimated locally from the double-log variogram is also mapped to illustrate how spatial variation changes across the data set. It is demonstrated that estimation of the variogram of residuals from local drift is worthwhile in this case for the characterisation of spatial variation. In addition, KT is shown to be useful for the assessment of uncertainty in predictions. This is shown to be true even when the sample grid is dense as is usually the case for remotely-sensed data. In addition, both ordinary kriging (OK) and KT are shown to provide more accurate predictions than inverse distance weighted (IDW) interpolation, used for comparative purposes.